i was bored one night and decided to fire up claude code. ended up learning about kalman filtering algorithms. applied one to eye-tracking data to smooth noisy gaze measurements and predict fixation targets. the filter works cleanly once you nail the noise covariance setup. fun visual application of bayesian state estimation.
posterior inference over conversion experiments using pymc. instead of p-values you get a full posterior over lift, which makes decision rules more principled and interpretable. includes credible intervals and expected loss calculations for making actual decisions rather than just rejecting null hypotheses.
exploration of mcmc sampling with pymc. i focused on understanding what the sampler is actually doing under the hood, diagnosing chain convergence, and visualizing posterior geometry across different model specifications. similar to hw in econ 491 bayesian ml course.
notes from econ 491 bayesian machine learning
notes on as-if, benchmarking and observability, volatile, compiler assumptions and more.
wrote a simple web server in C. code attached, and on github.
notes on c programming and memory management
notes on fastAPI fundementals, basic api methods, and how to build an api and handle query and path parameters cleanly..
studied backend development and crud operations. notes attached.
studied system design foundations and API architecture foundations. will go deeper into this later. notes attached.
practicing docker fudementals. writing dockerfiles, and spinning up containers in a home-lab style setup. notes attached.
self studying of kubernetes. not specifically to aquire the CKA or CKAD but to better understand containers and orchestration. topics include: architecture, yaml, manifests, making pods, namespaces, api versioning, resource monitoiring, requests and limits, probes, configmaps, volume mounting, network policies, ports and more. here are my notes as well.
practiced simulating failures in a github actions cicd pipeline, finding the root cause and resolving it. key idea is debugging when it looks good but doesn't work. notes attached.
git and github fundementals for the workplace. my notes.
notes of princicples of software testing. the testing pyramid and how to use modern ai tools to test software faster and more efficiently.
| Type | Title | Notes |
|---|---|---|
| project | kalman eye movement prediction(project) | i was bored one night and decided to fire up claude code. ended up learning about kalman filtering algorithms. applied one to eye-tracking data to smooth noisy gaze measurements and predict fixation targets. the filter works cleanly once you nail the noise covariance setup. fun visual application of bayesian state estimation. |
| project | bayesian a/b testing(project) | posterior inference over conversion experiments using pymc. instead of p-values you get a full posterior over lift, which makes decision rules more principled and interpretable. includes credible intervals and expected loss calculations for making actual decisions rather than just rejecting null hypotheses. |
| project | posterior draws in pymc(project) | exploration of mcmc sampling with pymc. i focused on understanding what the sampler is actually doing under the hood, diagnosing chain convergence, and visualizing posterior geometry across different model specifications. similar to hw in econ 491 bayesian ml course. |
| studies | bayesian ml class(studies) | notes from econ 491 bayesian machine learning |
| studies | c, compilers, ub, and optimization #1(studies) | notes on as-if, benchmarking and observability, volatile, compiler assumptions and more. |
| studies | simple web server in C(studies) | wrote a simple web server in C. code attached, and on github. |
| studies | c and memory management basics(studies) | notes on c programming and memory management |
| studies | fastAPI(studies) | notes on fastAPI fundementals, basic api methods, and how to build an api and handle query and path parameters cleanly.. |
| studies | backend development + crud(studies) | studied backend development and crud operations. notes attached. |
| studies | system design foundations(studies) | studied system design foundations and API architecture foundations. will go deeper into this later. notes attached. |
| studies | docker(studies) | practicing docker fudementals. writing dockerfiles, and spinning up containers in a home-lab style setup. notes attached. |
| studies | kubernetes(studies) | self studying of kubernetes. not specifically to aquire the CKA or CKAD but to better understand containers and orchestration. topics include: architecture, yaml, manifests, making pods, namespaces, api versioning, resource monitoiring, requests and limits, probes, configmaps, volume mounting, network policies, ports and more. here are my notes as well. |
| studies | devops/cicd failures(studies) | practiced simulating failures in a github actions cicd pipeline, finding the root cause and resolving it. key idea is debugging when it looks good but doesn't work. notes attached. |
| studies | git & github(studies) | git and github fundementals for the workplace. my notes. |
| studies | software testing practices(studies) | notes of princicples of software testing. the testing pyramid and how to use modern ai tools to test software faster and more efficiently. |